Pandas Profiling Report

Dataset statistics

Number of variables	40
Number of observations	3533211
Missing cells	69829472
Missing cells (%)	49.4%
Duplicate rows	0
Duplicate rows (%)	0.0%
Total size in memory	1.1 GiB
Average record size in memory	320.0 B

Variable types

Categorical	16
Numeric	18
Unsupported	6

Alerts

`id_mutation` has a high cardinality: 1514872 distinct values	High cardinality
`date_mutation` has a high cardinality: 365 distinct values	High cardinality
`adresse_nom_voie` has a high cardinality: 506794 distinct values	High cardinality
`adresse_code_voie` has a high cardinality: 16746 distinct values	High cardinality
`nom_commune` has a high cardinality: 30590 distinct values	High cardinality
`ancien_nom_commune` has a high cardinality: 192 distinct values	High cardinality
`id_parcelle` has a high cardinality: 2142850 distinct values	High cardinality
`ancien_id_parcelle` has a high cardinality: 3366 distinct values	High cardinality
`code_nature_culture_speciale` has a high cardinality: 120 distinct values	High cardinality
`nature_culture_speciale` has a high cardinality: 120 distinct values	High cardinality
`code_postal` is highly correlated with `ancien_code_commune`	High correlation
`ancien_code_commune` is highly correlated with `code_postal` and 1 other fields	High correlation
`lot1_surface_carrez` is highly correlated with `surface_reelle_bati` and 2 other fields	High correlation
`lot2_surface_carrez` is highly correlated with `lot3_surface_carrez` and 4 other fields	High correlation
`lot3_surface_carrez` is highly correlated with `lot2_surface_carrez` and 3 other fields	High correlation
`lot4_numero` is highly correlated with `ancien_code_commune` and 1 other fields	High correlation
`lot4_surface_carrez` is highly correlated with `lot2_surface_carrez` and 2 other fields	High correlation
`lot5_numero` is highly correlated with `lot4_numero`	High correlation
`lot5_surface_carrez` is highly correlated with `lot2_surface_carrez` and 2 other fields	High correlation
`code_type_local` is highly correlated with `nombre_pieces_principales`	High correlation
`surface_reelle_bati` is highly correlated with `lot1_surface_carrez` and 3 other fields	High correlation
`nombre_pieces_principales` is highly correlated with `lot1_surface_carrez` and 3 other fields	High correlation
`surface_terrain` is highly correlated with `lot1_surface_carrez`	High correlation
`code_postal` is highly correlated with `ancien_code_commune`	High correlation
`ancien_code_commune` is highly correlated with `code_postal` and 1 other fields	High correlation
`lot1_surface_carrez` is highly correlated with `lot5_surface_carrez`	High correlation
`lot2_surface_carrez` is highly correlated with `lot3_surface_carrez` and 1 other fields	High correlation
`lot3_surface_carrez` is highly correlated with `lot2_surface_carrez` and 2 other fields	High correlation
`lot4_numero` is highly correlated with `ancien_code_commune` and 1 other fields	High correlation
`lot4_surface_carrez` is highly correlated with `lot3_surface_carrez` and 1 other fields	High correlation
`lot5_numero` is highly correlated with `lot4_numero`	High correlation
`lot5_surface_carrez` is highly correlated with `lot1_surface_carrez` and 2 other fields	High correlation
`code_type_local` is highly correlated with `nombre_pieces_principales`	High correlation
`surface_reelle_bati` is highly correlated with `lot4_surface_carrez`	High correlation
`nombre_pieces_principales` is highly correlated with `code_type_local`	High correlation
`code_postal` is highly correlated with `ancien_code_commune`	High correlation
`ancien_code_commune` is highly correlated with `code_postal` and 1 other fields	High correlation
`lot1_surface_carrez` is highly correlated with `surface_reelle_bati` and 1 other fields	High correlation
`lot2_surface_carrez` is highly correlated with `lot5_surface_carrez` and 2 other fields	High correlation
`lot3_surface_carrez` is highly correlated with `lot4_surface_carrez` and 2 other fields	High correlation
`lot4_numero` is highly correlated with `ancien_code_commune` and 1 other fields	High correlation
`lot4_surface_carrez` is highly correlated with `lot3_surface_carrez` and 1 other fields	High correlation
`lot5_numero` is highly correlated with `lot4_numero`	High correlation
`lot5_surface_carrez` is highly correlated with `lot2_surface_carrez` and 2 other fields	High correlation
`code_type_local` is highly correlated with `nombre_pieces_principales`	High correlation
`surface_reelle_bati` is highly correlated with `lot1_surface_carrez` and 3 other fields	High correlation
`nombre_pieces_principales` is highly correlated with `lot1_surface_carrez` and 3 other fields	High correlation
`code_type_local` is highly correlated with `type_local`	High correlation
`code_nature_culture` is highly correlated with `nature_culture`	High correlation
`type_local` is highly correlated with `code_type_local`	High correlation
`nature_culture` is highly correlated with `code_nature_culture`	High correlation
`adresse_numero` is highly correlated with `adresse_suffixe`	High correlation
`adresse_suffixe` is highly correlated with `adresse_numero` and 1 other fields	High correlation
`code_postal` is highly correlated with `ancien_code_commune` and 1 other fields	High correlation
`ancien_code_commune` is highly correlated with `adresse_suffixe` and 1 other fields	High correlation
`lot1_surface_carrez` is highly correlated with `lot2_surface_carrez` and 3 other fields	High correlation
`lot2_surface_carrez` is highly correlated with `lot1_surface_carrez` and 3 other fields	High correlation
`lot3_surface_carrez` is highly correlated with `lot1_surface_carrez` and 3 other fields	High correlation
`lot4_numero` is highly correlated with `lot5_numero`	High correlation
`lot4_surface_carrez` is highly correlated with `lot1_surface_carrez` and 3 other fields	High correlation
`lot5_numero` is highly correlated with `lot4_numero`	High correlation
`lot5_surface_carrez` is highly correlated with `lot1_surface_carrez` and 3 other fields	High correlation
`code_type_local` is highly correlated with `type_local`	High correlation
`type_local` is highly correlated with `code_type_local`	High correlation
`code_nature_culture` is highly correlated with `nature_culture`	High correlation
`nature_culture` is highly correlated with `code_nature_culture`	High correlation
`longitude` is highly correlated with `code_postal` and 1 other fields	High correlation
`latitude` is highly correlated with `longitude`	High correlation
`valeur_fonciere` has 40825 (1.2%) missing values	Missing
`adresse_numero` has 1447761 (41.0%) missing values	Missing
`adresse_suffixe` has 3380766 (95.7%) missing values	Missing
`ancien_code_commune` has 3528985 (99.9%) missing values	Missing
`ancien_nom_commune` has 3528985 (99.9%) missing values	Missing
`ancien_id_parcelle` has 3529056 (99.9%) missing values	Missing
`numero_volume` has 3523727 (99.7%) missing values	Missing
`lot1_numero` has 2436238 (69.0%) missing values	Missing
`lot1_surface_carrez` has 3234737 (91.6%) missing values	Missing
`lot2_numero` has 3304923 (93.5%) missing values	Missing
`lot2_surface_carrez` has 3458801 (97.9%) missing values	Missing
`lot3_numero` has 3495391 (98.9%) missing values	Missing
`lot3_surface_carrez` has 3525820 (99.8%) missing values	Missing
`lot4_numero` has 3520085 (99.6%) missing values	Missing
`lot4_surface_carrez` has 3531180 (99.9%) missing values	Missing
`lot5_numero` has 3526863 (99.8%) missing values	Missing
`lot5_surface_carrez` has 3532265 (> 99.9%) missing values	Missing
`code_type_local` has 1632190 (46.2%) missing values	Missing
`type_local` has 1632190 (46.2%) missing values	Missing
`surface_reelle_bati` has 2090899 (59.2%) missing values	Missing
`nombre_pieces_principales` has 1634823 (46.3%) missing values	Missing
`code_nature_culture` has 1112059 (31.5%) missing values	Missing
`nature_culture` has 1112059 (31.5%) missing values	Missing
`code_nature_culture_speciale` has 3375916 (95.5%) missing values	Missing
`nature_culture_speciale` has 3375916 (95.5%) missing values	Missing
`surface_terrain` has 1112128 (31.5%) missing values	Missing
`longitude` has 51669 (1.5%) missing values	Missing
`latitude` has 51669 (1.5%) missing values	Missing
`numero_disposition` is highly skewed (γ1 = 81.2603909)	Skewed
`valeur_fonciere` is highly skewed (γ1 = 42.3720987)	Skewed
`lot1_surface_carrez` is highly skewed (γ1 = 44.33723987)	Skewed
`lot2_surface_carrez` is highly skewed (γ1 = 67.65985445)	Skewed
`lot4_numero` is highly skewed (γ1 = 75.84754127)	Skewed
`lot5_numero` is highly skewed (γ1 = 54.84380155)	Skewed
`nombre_lots` is highly skewed (γ1 = 39.52830246)	Skewed
`surface_reelle_bati` is highly skewed (γ1 = 162.9347308)	Skewed
`surface_terrain` is highly skewed (γ1 = 45.59182149)	Skewed
`ancien_id_parcelle` is uniformly distributed	Uniform
`code_commune` is an unsupported type, check if it needs cleaning or further analysis	Unsupported
`code_departement` is an unsupported type, check if it needs cleaning or further analysis	Unsupported
`numero_volume` is an unsupported type, check if it needs cleaning or further analysis	Unsupported
`lot1_numero` is an unsupported type, check if it needs cleaning or further analysis	Unsupported
`lot2_numero` is an unsupported type, check if it needs cleaning or further analysis	Unsupported
`lot3_numero` is an unsupported type, check if it needs cleaning or further analysis	Unsupported
`nombre_lots` has 2436238 (69.0%) zeros	Zeros
`nombre_pieces_principales` has 587272 (16.6%) zeros	Zeros

Reproduction

Analysis started	2021-10-05 22:08:48.357661
Analysis finished	2021-10-05 22:25:43.240396
Duration	16 minutes and 54.88 seconds
Software version	pandas-profiling v3.1.0
Download configuration	config.json

id_mutation
Categorical

HIGH CARDINALITY

Distinct	1514872
Distinct (%)	42.9%
Missing	0
Missing (%)	0.0%
Memory size	27.0 MiB

2019-171544	2778
2019-268092	2736
2019-384592	2164
2019-178592	2016
2019-1437512	1700
Other values (1514867)	3521817

Length

Max length	12
Median length	11
Mean length	11.24444422
Min length	6

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	726052 ?
Unique (%)	20.5%

Sample

1st row	2019-1
2nd row	2019-2
3rd row	2019-2
4th row	2019-3
5th row	2019-4

Common Values

Value	Count	Frequency (%)
2019-171544	2778	0.1%
2019-268092	2736	0.1%
2019-384592	2164	0.1%
2019-178592	2016	0.1%
2019-1437512	1700	< 0.1%
2019-1101871	1658	< 0.1%
2019-1325242	1543	< 0.1%
2019-1057935	1409	< 0.1%
2019-230952	1395	< 0.1%
2019-1044111	1271	< 0.1%
Other values (1514862)	3514541	99.5%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
2019-171544	2778	0.1%
2019-268092	2736	0.1%
2019-384592	2164	0.1%
2019-178592	2016	0.1%
2019-1437512	1700	< 0.1%
2019-1101871	1658	< 0.1%
2019-1325242	1543	< 0.1%
2019-1057935	1409	< 0.1%
2019-230952	1395	< 0.1%
2019-1044111	1271	< 0.1%
Other values (1514862)	3514541	99.5%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

date_mutation
Categorical

HIGH CARDINALITY

Distinct	365
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	27.0 MiB

2019-12-20	36454
2019-06-28	29693
2019-12-27	27606
2019-12-19	27075
2019-12-23	25723
Other values (360)	3386660

Length

Max length	10
Median length	10
Mean length	10
Min length	10

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	2 ?
Unique (%)	< 0.1%

Sample

1st row	2019-01-04
2nd row	2019-01-04
3rd row	2019-01-04
4th row	2019-01-08
5th row	2019-01-07

Common Values

Value	Count	Frequency (%)
2019-12-20	36454	1.0%
2019-06-28	29693	0.8%
2019-12-27	27606	0.8%
2019-12-19	27075	0.8%
2019-12-23	25723	0.7%
2019-03-29	25501	0.7%
2019-11-29	24992	0.7%
2019-12-30	24653	0.7%
2019-12-18	23998	0.7%
2019-05-29	23152	0.7%
Other values (355)	3264364	92.4%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
2019-12-20	36454	1.0%
2019-06-28	29693	0.8%
2019-12-27	27606	0.8%
2019-12-19	27075	0.8%
2019-12-23	25723	0.7%
2019-03-29	25501	0.7%
2019-11-29	24992	0.7%
2019-12-30	24653	0.7%
2019-12-18	23998	0.7%
2019-05-29	23152	0.7%
Other values (355)	3264364	92.4%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

numero_disposition
Real number (ℝ_≥0)

SKEWED

Distinct	627
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	1.18635966

Minimum	1
Maximum	694
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	27.0 MiB

Quantile statistics

Minimum	1
5-th percentile	1
Q1	1
median	1
Q3	1
95-th percentile	2
Maximum	694
Range	693
Interquartile range (IQR)	0

Descriptive statistics

Standard deviation	6.333766329
Coefficient of variation (CV)	5.338824763
Kurtosis	7182.774453
Mean	1.18635966
Median Absolute Deviation (MAD)	0
Skewness	81.2603909
Sum	4191659
Variance	40.11659592
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
1	3315151	93.8%
2	179269	5.1%
3	24353	0.7%
4	4631	0.1%
5	1743	< 0.1%
6	1250	< 0.1%
7	855	< 0.1%
10	469	< 0.1%
11	437	< 0.1%
9	364	< 0.1%
Other values (617)	4689	0.1%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
1	3315151	93.8%
2	179269	5.1%
3	24353	0.7%
4	4631	0.1%
5	1743	< 0.1%
6	1250	< 0.1%
7	855	< 0.1%
8	356	< 0.1%
9	364	< 0.1%
10	469	< 0.1%

Value	Count	Frequency (%)
694	1	< 0.1%
693	1	< 0.1%
692	1	< 0.1%
691	1	< 0.1%
690	1	< 0.1%
689	1	< 0.1%
688	1	< 0.1%
687	1	< 0.1%
686	1	< 0.1%
685	1	< 0.1%

nature_mutation
Categorical

Distinct	6
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	27.0 MiB

Vente	3205120
Vente en l'état futur d'achèvement	261337
Echange	41612
Vente terrain à bâtir	10758
Adjudication	10435

Length

Max length	34
Median length	5
Mean length	7.246897227
Min length	5

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Vente
2nd row	Vente
3rd row	Vente
4th row	Vente
5th row	Vente

Common Values

Value	Count	Frequency (%)
Vente	3205120	90.7%
Vente en l'état futur d'achèvement	261337	7.4%
Echange	41612	1.2%
Vente terrain à bâtir	10758	0.3%
Adjudication	10435	0.3%
Expropriation	3949	0.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
vente	3477215	75.4%
d'achèvement	261337	5.7%
futur	261337	5.7%
l'état	261337	5.7%
en	261337	5.7%
echange	41612	0.9%
bâtir	10758	0.2%
à	10758	0.2%
terrain	10758	0.2%
adjudication	10435	0.2%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

valeur_fonciere
Real number (ℝ_≥0)

MISSING
SKEWED

Distinct	138730
Distinct (%)	4.0%
Missing	40825
Missing (%)	1.2%
Infinite	0
Infinite (%)	0.0%
Mean	1027460.827

Minimum	0.01
Maximum	2086000000
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	27.0 MiB

Quantile statistics

Minimum	0.01
5-th percentile	2600
Q1	60000
median	149000
Q3	270000
95-th percentile	1500000
Maximum	2086000000
Range	2086000000
Interquartile range (IQR)	210000

Descriptive statistics

Standard deviation	8156290.693
Coefficient of variation (CV)	7.938298456
Kurtosis	5534.136597
Mean	1027460.827
Median Absolute Deviation (MAD)	100000
Skewness	42.3720987
Sum	3.588289806 × 10¹²
Variance	6.652507787 × 10¹³
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
100000	30089	0.9%
150000	29164	0.8%
120000	27417	0.8%
1	27396	0.8%
80000	25365	0.7%
200000	24130	0.7%
130000	24114	0.7%
110000	23723	0.7%
50000	23545	0.7%
140000	23154	0.7%
Other values (138720)	3234289	91.5%
(Missing)	40825	1.2%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0.01	3	< 0.1%
0.1	12	< 0.1%
0.15	398	< 0.1%
0.16	3	< 0.1%
0.18	36	< 0.1%
0.19	2	< 0.1%
0.3	4	< 0.1%
0.33	8	< 0.1%
0.34	3	< 0.1%
0.5	20	< 0.1%

Value	Count	Frequency (%)
2086000000	2	< 0.1%
1750000000	3	< 0.1%
845000000	2	< 0.1%
690186750	24	< 0.1%
685667970	31	< 0.1%
612990460	6	< 0.1%
594609600	3	< 0.1%
527400000	5	< 0.1%
400000000	1	< 0.1%
385000000	1	< 0.1%

adresse_numero
Real number (ℝ_≥0)

HIGH CORRELATION
MISSING

Distinct	7299
Distinct (%)	0.3%
Missing	1447761
Missing (%)	41.0%
Infinite	0
Infinite (%)	0.0%
Mean	770.1700909

Minimum	1
Maximum	9999
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	27.0 MiB

Quantile statistics

Minimum	1
5-th percentile	2
Q1	8
median	26
Q3	100
95-th percentile	5727
Maximum	9999
Range	9998
Interquartile range (IQR)	92

Descriptive statistics

Standard deviation	2115.060468
Coefficient of variation (CV)	2.746225143
Kurtosis	7.513289879
Mean	770.1700909
Median Absolute Deviation (MAD)	22
Skewness	2.943936252
Sum	1606151216
Variance	4473480.782
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
1	93526	2.6%
2	81794	2.3%
3	65678	1.9%
4	64887	1.8%
5	58320	1.7%
6	57097	1.6%
7	50952	1.4%
8	50044	1.4%
9	46163	1.3%
10	45629	1.3%
Other values (7289)	1471360	41.6%
(Missing)	1447761	41.0%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
1	93526	2.6%
2	81794	2.3%
3	65678	1.9%
4	64887	1.8%
5	58320	1.7%
6	57097	1.6%
7	50952	1.4%
8	50044	1.4%
9	46163	1.3%
10	45629	1.3%

Value	Count	Frequency (%)
9999	491	< 0.1%
9998	93	< 0.1%
9997	17	< 0.1%
9996	21	< 0.1%
9995	21	< 0.1%
9994	14	< 0.1%
9993	3	< 0.1%
9992	7	< 0.1%
9991	20	< 0.1%
9990	10	< 0.1%

adresse_suffixe
Categorical

HIGH CORRELATION
MISSING

Distinct	40
Distinct (%)	< 0.1%
Missing	3380766
Missing (%)	95.7%
Memory size	27.0 MiB

B	88283
A	24458
F	13635
T	11587
C	5152
Other values (35)	9330

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1 ?
Unique (%)	< 0.1%

Sample

1st row	B
2nd row	Z
3rd row	B
4th row	B
5th row	A

Common Values

Value	Count	Frequency (%)
B	88283	2.5%
A	24458	0.7%
F	13635	0.4%
T	11587	0.3%
C	5152	0.1%
D	2439	0.1%
E	1395	< 0.1%
Q	1275	< 0.1%
P	724	< 0.1%
G	609	< 0.1%
Other values (30)	2888	0.1%
(Missing)	3380766	95.7%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
b	88283	57.9%
a	24458	16.0%
f	13635	8.9%
t	11587	7.6%
c	5152	3.4%
d	2439	1.6%
e	1395	0.9%
q	1275	0.8%
p	724	0.5%
g	609	0.4%
Other values (27)	2888	1.9%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

adresse_nom_voie
Categorical

HIGH CARDINALITY

Distinct	506794
Distinct (%)	14.5%
Missing	33838
Missing (%)	1.0%
Memory size	27.0 MiB

LE VILLAGE	32178
LE BOURG	28220
AV JEAN JAURES	7143
GR GRANDE RUE	7114
RUE DE LA REPUBLIQUE	6371
Other values (506789)	3418347

Length

Max length	31
Median length	14
Mean length	14.72676219
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	172968 ?
Unique (%)	4.9%

Sample

1st row	RUE DE MONTHOLON
2nd row	RUE GEN DELESTRAINT
3rd row	RUE GEN DELESTRAINT
4th row	RUE DES CHAMPAGNES
5th row	LOT LE BIOLAY

Common Values

Value	Count	Frequency (%)
LE VILLAGE	32178	0.9%
LE BOURG	28220	0.8%
AV JEAN JAURES	7143	0.2%
GR GRANDE RUE	7114	0.2%
RUE DE LA REPUBLIQUE	6371	0.2%
RUE JEAN JAURES	6156	0.2%
RUE PASTEUR	5574	0.2%
RUE VICTOR HUGO	5201	0.1%
AV DE LA REPUBLIQUE	5129	0.1%
RUE DE PARIS	4361	0.1%
Other values (506784)	3391926	96.0%
(Missing)	33838	1.0%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
rue	1177070	11.7%
de	768672	7.6%
la	519788	5.2%
du	353758	3.5%
le	306217	3.0%
des	301752	3.0%
av	270241	2.7%
les	240278	2.4%
che	113774	1.1%
rte	111467	1.1%
Other values (209127)	5908361	58.7%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

adresse_code_voie
Categorical

HIGH CARDINALITY

Distinct	16746
Distinct (%)	0.5%
Missing	33771
Missing (%)	1.0%
Memory size	27.0 MiB

B005	15947
B007	15302
B003	15299
B014	15037
B017	14877
Other values (16741)	3422978

Length

Max length	4
Median length	4
Mean length	4
Min length	4

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1504 ?
Unique (%)	< 0.1%

Sample

1st row	2730
2nd row	1650
3rd row	1650
4th row	0043
5th row	A003

Common Values

Value	Count	Frequency (%)
B005	15947	0.5%
B007	15302	0.4%
B003	15299	0.4%
B014	15037	0.4%
B017	14877	0.4%
B006	14826	0.4%
B002	14820	0.4%
B010	14740	0.4%
B001	14734	0.4%
0020	14702	0.4%
Other values (16736)	3349156	94.8%
(Missing)	33771	1.0%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
b005	15947	0.5%
b007	15302	0.4%
b003	15299	0.4%
b014	15037	0.4%
b017	14877	0.4%
b006	14826	0.4%
b002	14820	0.4%
b010	14740	0.4%
b001	14734	0.4%
0020	14702	0.4%
Other values (16736)	3349156	95.7%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

code_postal
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	5862
Distinct (%)	0.2%
Missing	33937
Missing (%)	1.0%
Infinite	0
Infinite (%)	0.0%
Mean	50443.2464

Minimum	1000
Maximum	97490
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	27.0 MiB

Quantile statistics

Minimum	1000
5-th percentile	6540
Q1	29200
median	49280
Q3	75016
95-th percentile	93130
Maximum	97490
Range	96490
Interquartile range (IQR)	45816

Descriptive statistics

Standard deviation	27505.41514
Coefficient of variation (CV)	0.5452744838
Kurtosis	-1.200231695
Mean	50443.2464
Median Absolute Deviation (MAD)	24060
Skewness	-0.006414740661
Sum	1.765147406 × 10¹¹
Variance	756547862.1
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
21000	8593	0.2%
69100	8256	0.2%
75015	7867	0.2%
18000	7830	0.2%
54000	7612	0.2%
31200	7175	0.2%
75016	7019	0.2%
51100	6925	0.2%
35000	6733	0.2%
29200	6570	0.2%
Other values (5852)	3424694	96.9%
(Missing)	33937	1.0%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
1000	1892	0.1%
1090	462	< 0.1%
1100	1153	< 0.1%
1110	807	< 0.1%
1120	920	< 0.1%
1130	453	< 0.1%
1140	646	< 0.1%
1150	1158	< 0.1%
1160	896	< 0.1%
1170	2302	0.1%

Value	Count	Frequency (%)
97490	1855	0.1%
97480	613	< 0.1%
97470	388	< 0.1%
97460	732	< 0.1%
97450	271	< 0.1%
97442	47	< 0.1%
97441	370	< 0.1%
97440	879	< 0.1%
97439	114	< 0.1%
97438	644	< 0.1%

code_commune
Unsupported

REJECTED
UNSUPPORTED

Missing	0
Missing (%)	0.0%
Memory size	27.0 MiB

nom_commune
Categorical

HIGH CARDINALITY

Distinct	30590
Distinct (%)	0.9%
Missing	0
Missing (%)	0.0%
Memory size	27.0 MiB

Toulouse	29142
Nice	18541
Nantes	16670
Montpellier	14816
Bordeaux	13574
Other values (30585)	3440468

Length

Max length	45
Median length	10
Mean length	11.89568299
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	334 ?
Unique (%)	< 0.1%

Sample

1st row	Bourg-en-Bresse
2nd row	Bourg-en-Bresse
3rd row	Bourg-en-Bresse
4th row	Priay
5th row	Saint-Étienne-du-Bois

Common Values

Value	Count	Frequency (%)
Toulouse	29142	0.8%
Nice	18541	0.5%
Nantes	16670	0.5%
Montpellier	14816	0.4%
Bordeaux	13574	0.4%
Lille	12182	0.3%
Rennes	11384	0.3%
Nîmes	8921	0.3%
Le Havre	8842	0.3%
Dijon	8668	0.2%
Other values (30580)	3390471	96.0%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
arrondissement	124276	3.0%
la	108063	2.6%
le	102566	2.5%
paris	68183	1.7%
les	38342	0.9%
marseille	34357	0.8%
toulouse	29142	0.7%
lyon	21736	0.5%
nice	18541	0.5%
nantes	16670	0.4%
Other values (30496)	3539720	86.3%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

code_departement
Unsupported

REJECTED
UNSUPPORTED

Missing	0
Missing (%)	0.0%
Memory size	27.0 MiB

ancien_code_commune
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct	192
Distinct (%)	4.5%
Missing	3528985
Missing (%)	99.9%
Infinite	0
Infinite (%)	0.0%
Mean	52133.70303

Minimum	1059
Maximum	91182
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	27.0 MiB

Quantile statistics

Minimum	1059
5-th percentile	1414
Q1	35011
median	50516
Q3	78884
95-th percentile	89448
Maximum	91182
Range	90123
Interquartile range (IQR)	43873

Descriptive statistics

Standard deviation	26055.09046
Coefficient of variation (CV)	0.4997744058
Kurtosis	-0.8447448861
Mean	52133.70303
Median Absolute Deviation (MAD)	22404
Skewness	-0.2432193738
Sum	220317029
Variance	678867738.6
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
91182	188	< 0.1%
49065	186	< 0.1%
53014	152	< 0.1%
89448	136	< 0.1%
41257	111	< 0.1%
78251	109	< 0.1%
78524	76	< 0.1%
50581	72	< 0.1%
14666	71	< 0.1%
79171	67	< 0.1%
Other values (182)	3058	0.1%
(Missing)	3528985	99.9%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
1059	3	< 0.1%
1091	63	< 0.1%
1097	26	< 0.1%
1122	39	< 0.1%
1186	4	< 0.1%
1205	28	< 0.1%
1218	13	< 0.1%
1221	5	< 0.1%
1341	11	< 0.1%
1413	4	< 0.1%

Value	Count	Frequency (%)
91182	188	< 0.1%
90073	1	< 0.1%
89448	136	< 0.1%
89381	14	< 0.1%
89340	11	< 0.1%
89109	2	< 0.1%
87184	17	< 0.1%
87173	45	< 0.1%
86278	61	< 0.1%
86188	24	< 0.1%

ancien_nom_commune
Categorical

HIGH CARDINALITY
MISSING

Distinct	192
Distinct (%)	4.5%
Missing	3528985
Missing (%)	99.9%
Memory size	27.0 MiB

Courcouronnes	188
Champigné	186
Azé	152
Vignes	136
Thenay	111
Other values (187)	3453

Length

Max length	26
Median length	10
Mean length	11.98414576
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	12 ?
Unique (%)	0.3%

Sample

1st row	Lancrans
2nd row	Lancrans
3rd row	Châtillon-en-Michaille
4th row	Châtillon-en-Michaille
5th row	Lancrans

Common Values

Value	Count	Frequency (%)
Courcouronnes	188	< 0.1%
Champigné	186	< 0.1%
Azé	152	< 0.1%
Vignes	136	< 0.1%
Thenay	111	< 0.1%
Fourqueux	109	< 0.1%
Rocquencourt	76	< 0.1%
Soulles	72	< 0.1%
Sannerville	71	< 0.1%
Mauzé-Thouarsais	67	< 0.1%
Other values (182)	3058	0.1%
(Missing)	3528985	99.9%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
courcouronnes	188	4.2%
champigné	186	4.1%
le	173	3.8%
azé	152	3.4%
vignes	136	3.0%
thenay	111	2.5%
fourqueux	109	2.4%
la	78	1.7%
rocquencourt	76	1.7%
soulles	72	1.6%
Other values (185)	3232	71.6%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

id_parcelle
Categorical

HIGH CARDINALITY

Distinct	2142850
Distinct (%)	60.6%
Missing	0
Missing (%)	0.0%
Memory size	27.0 MiB

95280000AC0239	1693
91345000AO0357	1044
783220000F0122	1013
910270000E0576	971
930530000J0092	806
Other values (2142845)	3527684

Length

Max length	14
Median length	14
Mean length	14
Min length	14

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1709064 ?
Unique (%)	48.4%

Sample

1st row	01053000AI0298
2nd row	01053000AM0095
3rd row	01053000AM0095
4th row	013140000E1676
5th row	01350000AA0011

Common Values

Value	Count	Frequency (%)
95280000AC0239	1693	< 0.1%
91345000AO0357	1044	< 0.1%
783220000F0122	1013	< 0.1%
910270000E0576	971	< 0.1%
930530000J0092	806	< 0.1%
78242000AC0403	697	< 0.1%
93031000AU0124	687	< 0.1%
13001000IX0113	630	< 0.1%
75114000DM0007	595	< 0.1%
30189000EM0022	502	< 0.1%
Other values (2142840)	3524573	99.8%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
95280000ac0239	1693	< 0.1%
91345000ao0357	1044	< 0.1%
783220000f0122	1013	< 0.1%
910270000e0576	971	< 0.1%
930530000j0092	806	< 0.1%
78242000ac0403	697	< 0.1%
93031000au0124	687	< 0.1%
13001000ix0113	630	< 0.1%
75114000dm0007	595	< 0.1%
30189000em0022	502	< 0.1%
Other values (2142840)	3524573	99.8%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

ancien_id_parcelle
Categorical

HIGH CARDINALITY
MISSING
UNIFORM

Distinct	3366
Distinct (%)	81.0%
Missing	3529056
Missing (%)	99.9%
Memory size	27.0 MiB

782510000B0256	32
78524000AD0005	19
78524000AB0143	15
91182000AP0094	14
78524000AB0101	14
Other values (3361)	4061

Length

Max length	14
Median length	14
Mean length	14
Min length	14

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	2882 ?
Unique (%)	69.4%

Sample

1st row	012050000E1483
2nd row	012050000E1490
3rd row	010910000A1095
4th row	010910000A1104
5th row	012050000E1401

Common Values

Value	Count	Frequency (%)
782510000B0256	32	< 0.1%
78524000AD0005	19	< 0.1%
78524000AB0143	15	< 0.1%
91182000AP0094	14	< 0.1%
78524000AB0101	14	< 0.1%
691470000U0362	12	< 0.1%
91182000AP0087	12	< 0.1%
91182000AP0046	10	< 0.1%
91182000AP0091	9	< 0.1%
91182000AN0028	8	< 0.1%
Other values (3356)	4010	0.1%
(Missing)	3529056	99.9%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
782510000b0256	32	0.8%
78524000ad0005	19	0.5%
78524000ab0143	15	0.4%
91182000ap0094	14	0.3%
78524000ab0101	14	0.3%
691470000u0362	12	0.3%
91182000ap0087	12	0.3%
91182000ap0046	10	0.2%
91182000ap0091	9	0.2%
91182000ap0059	8	0.2%
Other values (3356)	4010	96.5%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

numero_volume
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing	3523727
Missing (%)	99.7%
Memory size	27.0 MiB

lot1_numero
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing	2436238
Missing (%)	69.0%
Memory size	27.0 MiB

lot1_surface_carrez
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING
SKEWED

Distinct	18559
Distinct (%)	6.2%
Missing	3234737
Missing (%)	91.6%
Infinite	0
Infinite (%)	0.0%
Mean	61.73629629

Minimum	0.14
Maximum	9646.2
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	27.0 MiB

Quantile statistics

Minimum	0.14
5-th percentile	16.28
Q1	33.62
median	53.045
Q3	72.94
95-th percentile	116.44
Maximum	9646.2
Range	9646.06
Interquartile range (IQR)	39.32

Descriptive statistics

Standard deviation	113.0510994
Coefficient of variation (CV)	1.831193417
Kurtosis	2712.421666
Mean	61.73629629
Median Absolute Deviation (MAD)	19.625
Skewness	44.33723987
Sum	18426679.3
Variance	12780.55107
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
12.5	1215	< 0.1%
12	643	< 0.1%
15	373	< 0.1%
13	350	< 0.1%
10	328	< 0.1%
30	284	< 0.1%
40	278	< 0.1%
20	271	< 0.1%
25	268	< 0.1%
14	265	< 0.1%
Other values (18549)	294199	8.3%
(Missing)	3234737	91.6%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0.14	1	< 0.1%
0.26	1	< 0.1%
0.36	1	< 0.1%
0.5	1	< 0.1%
0.61	1	< 0.1%
0.64	1	< 0.1%
0.7	1	< 0.1%
0.74	1	< 0.1%
0.8	1	< 0.1%
0.85	1	< 0.1%

Value	Count	Frequency (%)
9646.2	1	< 0.1%
9101	1	< 0.1%
8946	1	< 0.1%
8875.2	1	< 0.1%
8771.94	1	< 0.1%
8719.9	1	< 0.1%
7717	1	< 0.1%
7634	1	< 0.1%
7597.7	19	< 0.1%
6422.87	1	< 0.1%

lot2_numero
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing	3304923
Missing (%)	93.5%
Memory size	27.0 MiB

lot2_surface_carrez
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING
SKEWED

Distinct	12485
Distinct (%)	16.8%
Missing	3458801
Missing (%)	97.9%
Infinite	0
Infinite (%)	0.0%
Mean	63.44957197

Minimum	0.13
Maximum	8630
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	27.0 MiB

Quantile statistics

Minimum	0.13
5-th percentile	23
Q1	43
median	61.08
Q3	76.26
95-th percentile	110.1
Maximum	8630
Range	8629.87
Interquartile range (IQR)	33.26

Descriptive statistics

Standard deviation	53.40071893
Coefficient of variation (CV)	0.8416245733
Kurtosis	9455.510397
Mean	63.44957197
Median Absolute Deviation (MAD)	16.78
Skewness	67.65985445
Sum	4721282.65
Variance	2851.636783
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
69.16	105	< 0.1%
74.83	99	< 0.1%
20.43	71	< 0.1%
65	67	< 0.1%
55	64	< 0.1%
67	61	< 0.1%
68	59	< 0.1%
70	58	< 0.1%
50	57	< 0.1%
54	55	< 0.1%
Other values (12475)	73714	2.1%
(Missing)	3458801	97.9%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0.13	1	< 0.1%
0.3	1	< 0.1%
0.54	1	< 0.1%
0.58	1	< 0.1%
0.63	1	< 0.1%
0.75	1	< 0.1%
0.8	4	< 0.1%
0.9	2	< 0.1%
0.91	1	< 0.1%
0.93	1	< 0.1%

Value	Count	Frequency (%)
8630	1	< 0.1%
3583.64	1	< 0.1%
3006.59	1	< 0.1%
2520	1	< 0.1%
2111.68	1	< 0.1%
1989.7	1	< 0.1%
1828.92	1	< 0.1%
1584.42	1	< 0.1%
1505.32	1	< 0.1%
1474.6	1	< 0.1%

lot3_numero
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing	3495391
Missing (%)	98.9%
Memory size	27.0 MiB

lot3_surface_carrez
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct	5133
Distinct (%)	69.4%
Missing	3525820
Missing (%)	99.8%
Infinite	0
Infinite (%)	0.0%
Mean	72.66339196

Minimum	0.85
Maximum	3583.64
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	27.0 MiB

Quantile statistics

Minimum	0.85
5-th percentile	14.085
Q1	38.425
median	60.76
Q3	85.21
95-th percentile	167.43
Maximum	3583.64
Range	3582.79
Interquartile range (IQR)	46.785

Descriptive statistics

Standard deviation	82.71852482
Coefficient of variation (CV)	1.138379624
Kurtosis	547.2276462
Mean	72.66339196
Median Absolute Deviation (MAD)	23.15
Skewness	16.83892817
Sum	537055.13
Variance	6842.354349
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
52.31	91	< 0.1%
20.61	69	< 0.1%
12.5	21	< 0.1%
195.18	21	< 0.1%
15	15	< 0.1%
66.11	14	< 0.1%
40	12	< 0.1%
12	12	< 0.1%
19	11	< 0.1%
20	11	< 0.1%
Other values (5123)	7114	0.2%
(Missing)	3525820	99.8%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0.85	1	< 0.1%
1	7	< 0.1%
1.13	1	< 0.1%
1.22	1	< 0.1%
1.25	1	< 0.1%
1.3	1	< 0.1%
1.33	1	< 0.1%
1.35	1	< 0.1%
1.53	1	< 0.1%
1.78	1	< 0.1%

Value	Count	Frequency (%)
3583.64	1	< 0.1%
2128.86	1	< 0.1%
1699.39	1	< 0.1%
1480.16	1	< 0.1%
1300	1	< 0.1%
1240	1	< 0.1%
1132.3	1	< 0.1%
1055	1	< 0.1%
918.1	1	< 0.1%
889	1	< 0.1%

lot4_numero
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING
SKEWED

Distinct	804
Distinct (%)	6.1%
Missing	3520085
Missing (%)	99.6%
Infinite	0
Infinite (%)	0.0%
Mean	141.2614658

Minimum	2
Maximum	191612
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	27.0 MiB

Quantile statistics

Minimum	2
5-th percentile	4
Q1	7
median	24
Q3	71
95-th percentile	411
Maximum	191612
Range	191610
Interquartile range (IQR)	64

Descriptive statistics

Standard deviation	2245.813621
Coefficient of variation (CV)	15.89827494
Kurtosis	6072.676851
Mean	141.2614658
Median Absolute Deviation (MAD)	19
Skewness	75.84754127
Sum	1854198
Variance	5043678.822
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
9	783	< 0.1%
8	733	< 0.1%
7	722	< 0.1%
4	681	< 0.1%
6	678	< 0.1%
5	631	< 0.1%
3	323	< 0.1%
2	249	< 0.1%
13	223	< 0.1%
17	150	< 0.1%
Other values (794)	7953	0.2%
(Missing)	3520085	99.6%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
2	249	< 0.1%
3	323	< 0.1%
4	681	< 0.1%
5	631	< 0.1%
6	678	< 0.1%
7	722	< 0.1%
8	733	< 0.1%
9	783	< 0.1%
11	8	< 0.1%
12	118	< 0.1%

Value	Count	Frequency (%)
191612	1	< 0.1%
161816	1	< 0.1%
20035	1	< 0.1%
17014	1	< 0.1%
11279	1	< 0.1%
11045	1	< 0.1%
11043	1	< 0.1%
11041	1	< 0.1%
10729	1	< 0.1%
10520	1	< 0.1%

lot4_surface_carrez
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct	1558
Distinct (%)	76.7%
Missing	3531180
Missing (%)	99.9%
Infinite	0
Infinite (%)	0.0%
Mean	88.28162974

Minimum	1
Maximum	5107.9
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	27.0 MiB

Quantile statistics

Minimum	1
5-th percentile	11.52
Q1	33.285
median	65.09
Q3	97.635
95-th percentile	210.42
Maximum	5107.9
Range	5106.9
Interquartile range (IQR)	64.35

Descriptive statistics

Standard deviation	175.4470496
Coefficient of variation (CV)	1.987356261
Kurtosis	398.0506412
Mean	88.28162974
Median Absolute Deviation (MAD)	32.07
Skewness	16.78892705
Sum	179299.99
Variance	30781.66721
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
74.87	90	< 0.1%
20.99	68	< 0.1%
115.75	21	< 0.1%
51.44	14	< 0.1%
63.88	13	< 0.1%
12.5	10	< 0.1%
20	8	< 0.1%
53.93	8	< 0.1%
57.92	7	< 0.1%
14.84	6	< 0.1%
Other values (1548)	1786	0.1%
(Missing)	3531180	99.9%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
1	3	< 0.1%
1.55	1	< 0.1%
1.6	1	< 0.1%
1.8	1	< 0.1%
2	1	< 0.1%
2.33	1	< 0.1%
2.87	1	< 0.1%
3.09	1	< 0.1%
3.4	1	< 0.1%
3.65	1	< 0.1%

Value	Count	Frequency (%)
5107.9	1	< 0.1%
3208.9	1	< 0.1%
2023	1	< 0.1%
1612	1	< 0.1%
1588.65	1	< 0.1%
1588.25	1	< 0.1%
1415.96	1	< 0.1%
1362.6	1	< 0.1%
1300	1	< 0.1%
1055	1	< 0.1%

lot5_numero
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING
SKEWED

Distinct	585
Distinct (%)	9.2%
Missing	3526863
Missing (%)	99.8%
Infinite	0
Infinite (%)	0.0%
Mean	183.1717076

Minimum	2
Maximum	191613
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	27.0 MiB

Quantile statistics

Minimum	2
5-th percentile	4
Q1	8
median	28
Q3	82
95-th percentile	576.65
Maximum	191613
Range	191611
Interquartile range (IQR)	74

Descriptive statistics

Standard deviation	3186.490293
Coefficient of variation (CV)	17.39619254
Kurtosis	3098.016362
Mean	183.1717076
Median Absolute Deviation (MAD)	22
Skewness	54.84380155
Sum	1162774
Variance	10153720.39
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
9	366	< 0.1%
8	360	< 0.1%
5	339	< 0.1%
6	305	< 0.1%
7	302	< 0.1%
4	191	< 0.1%
3	154	< 0.1%
14	132	< 0.1%
705	91	< 0.1%
2	82	< 0.1%
Other values (575)	4026	0.1%
(Missing)	3526863	99.8%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
2	82	< 0.1%
3	154	< 0.1%
4	191	< 0.1%
5	339	< 0.1%
6	305	< 0.1%
7	302	< 0.1%
8	360	< 0.1%
9	366	< 0.1%
11	1	< 0.1%
12	3	< 0.1%

Value	Count	Frequency (%)
191613	1	< 0.1%
161915	1	< 0.1%
20036	1	< 0.1%
11046	1	< 0.1%
7062	1	< 0.1%
7036	2	< 0.1%
7005	2	< 0.1%
6175	1	< 0.1%
6074	1	< 0.1%
6034	1	< 0.1%

lot5_surface_carrez
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct	676
Distinct (%)	71.5%
Missing	3532265
Missing (%)	> 99.9%
Infinite	0
Infinite (%)	0.0%
Mean	91.14411205

Minimum	0.89
Maximum	1029.55
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	27.0 MiB

Quantile statistics

Minimum	0.89
5-th percentile	11.4875
Q1	26.925
median	74.1
Q3	107.135
95-th percentile	278.3975
Maximum	1029.55
Range	1028.66
Interquartile range (IQR)	80.21

Descriptive statistics

Standard deviation	102.5548555
Coefficient of variation (CV)	1.125194521
Kurtosis	17.67653912
Mean	91.14411205
Median Absolute Deviation (MAD)	41.92
Skewness	3.473662083
Sum	86222.33
Variance	10517.49838
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
77	90	< 0.1%
23.79	68	< 0.1%
116.1	21	< 0.1%
32.67	13	< 0.1%
34.84	7	< 0.1%
12.5	7	< 0.1%
55.15	7	< 0.1%
21.44	6	< 0.1%
12	5	< 0.1%
21.1	4	< 0.1%
Other values (666)	718	< 0.1%
(Missing)	3532265	> 99.9%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0.89	1	< 0.1%
0.97	1	< 0.1%
1.3	1	< 0.1%
2	1	< 0.1%
2.08	1	< 0.1%
2.23	1	< 0.1%
2.96	1	< 0.1%
3.2	1	< 0.1%
3.8	3	< 0.1%
3.91	1	< 0.1%

Value	Count	Frequency (%)
1029.55	1	< 0.1%
818.8	1	< 0.1%
769	1	< 0.1%
671.9	1	< 0.1%
662.35	1	< 0.1%
635.69	1	< 0.1%
613.7	1	< 0.1%
603.04	1	< 0.1%
567.43	1	< 0.1%
509.15	1	< 0.1%

nombre_lots
Real number (ℝ_≥0)

SKEWED
ZEROS

Distinct	86
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	0.3993333543

Minimum	0
Maximum	175
Zeros	2436238
Zeros (%)	69.0%
Negative	0
Negative (%)	0.0%
Memory size	27.0 MiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	0
Q3	1
95-th percentile	2
Maximum	175
Range	175
Interquartile range (IQR)	1

Descriptive statistics

Standard deviation	0.9237460492
Coefficient of variation (CV)	2.313220369
Kurtosis	3942.605237
Mean	0.3993333543
Median Absolute Deviation (MAD)	0
Skewness	39.52830246
Sum	1410929
Variance	0.8533067635
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	2436238	69.0%
1	868685	24.6%
2	190468	5.4%
3	24694	0.7%
4	6778	0.2%
5	2526	0.1%
6	1280	< 0.1%
7	679	< 0.1%
8	433	< 0.1%
9	278	< 0.1%
Other values (76)	1152	< 0.1%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	2436238	69.0%
1	868685	24.6%
2	190468	5.4%
3	24694	0.7%
4	6778	0.2%
5	2526	0.1%
6	1280	< 0.1%
7	679	< 0.1%
8	433	< 0.1%
9	278	< 0.1%

Value	Count	Frequency (%)
175	1	< 0.1%
159	1	< 0.1%
150	1	< 0.1%
142	1	< 0.1%
141	1	< 0.1%
136	1	< 0.1%
118	1	< 0.1%
114	1	< 0.1%
110	1	< 0.1%
104	2	< 0.1%

code_type_local
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct	4
Distinct (%)	< 0.1%
Missing	1632190
Missing (%)	46.2%
Memory size	27.0 MiB

1.0	698631
2.0	614886
3.0	450801
4.0	136703

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	2.0
2nd row	3.0
3rd row	2.0
4th row	1.0
5th row	1.0

Common Values

Value	Count	Frequency (%)
1.0	698631	19.8%
2.0	614886	17.4%
3.0	450801	12.8%
4.0	136703	3.9%
(Missing)	1632190	46.2%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1.0	698631	36.8%
2.0	614886	32.3%
3.0	450801	23.7%
4.0	136703	7.2%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

type_local
Categorical

HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct	4
Distinct (%)	< 0.1%
Missing	1632190
Missing (%)	46.2%
Memory size	27.0 MiB

Maison	698631
Appartement	614886
Dépendance	450801
Local industriel. commercial ou assimilé	136703

Length

Max length	40
Median length	10
Mean length	11.01074738
Min length	6

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Appartement
2nd row	Dépendance
3rd row	Appartement
4th row	Maison
5th row	Maison

Common Values

Value	Count	Frequency (%)
Maison	698631	19.8%
Appartement	614886	17.4%
Dépendance	450801	12.8%
Local industriel. commercial ou assimilé	136703	3.9%
(Missing)	1632190	46.2%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
maison	698631	28.5%
appartement	614886	25.1%
dépendance	450801	18.4%
assimilé	136703	5.6%
ou	136703	5.6%
commercial	136703	5.6%
industriel	136703	5.6%
local	136703	5.6%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

surface_reelle_bati
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING
SKEWED

Distinct	4598
Distinct (%)	0.3%
Missing	2090899
Missing (%)	59.2%
Infinite	0
Infinite (%)	0.0%
Mean	114.5582745

Minimum	1
Maximum	312962
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	27.0 MiB

Quantile statistics

Minimum	1
5-th percentile	21
Q1	49
median	75
Q3	104
95-th percentile	190
Maximum	312962
Range	312961
Interquartile range (IQR)	55

Descriptive statistics

Standard deviation	909.0004014
Coefficient of variation (CV)	7.934829723
Kurtosis	40237.20298
Mean	114.5582745
Median Absolute Deviation (MAD)	27
Skewness	162.9347308
Sum	165228774
Variance	826281.7298
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
80	28149	0.8%
60	26035	0.7%
90	25149	0.7%
70	25027	0.7%
100	21679	0.6%
50	21599	0.6%
65	20212	0.6%
40	19079	0.5%
75	17538	0.5%
30	16977	0.5%
Other values (4588)	1220868	34.6%
(Missing)	2090899	59.2%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
1	345	< 0.1%
2	448	< 0.1%
3	356	< 0.1%
4	229	< 0.1%
5	327	< 0.1%
6	436	< 0.1%
7	356	< 0.1%
8	1074	< 0.1%
9	1140	< 0.1%
10	3914	0.1%

Value	Count	Frequency (%)
312962	2	< 0.1%
240000	2	< 0.1%
215000	2	< 0.1%
212120	2	< 0.1%
152856	6	< 0.1%
142536	1	< 0.1%
142124	1	< 0.1%
112755	1	< 0.1%
107476	1	< 0.1%
104760	1	< 0.1%

nombre_pieces_principales
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING
ZEROS

Distinct	40
Distinct (%)	< 0.1%
Missing	1634823
Missing (%)	46.3%
Infinite	0
Infinite (%)	0.0%
Mean	2.3919852

Minimum	0
Maximum	67
Zeros	587272
Zeros (%)	16.6%
Negative	0
Negative (%)	0.0%
Memory size	27.0 MiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	2
Q3	4
95-th percentile	6
Maximum	67
Range	67
Interquartile range (IQR)	4

Descriptive statistics

Standard deviation	2.079934991
Coefficient of variation (CV)	0.86954342
Kurtosis	2.596047971
Mean	2.3919852
Median Absolute Deviation (MAD)	2
Skewness	0.5953746862
Sum	4540916
Variance	4.326129569
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=40)

Value	Count	Frequency (%)
0	587272	16.6%
4	320521	9.1%
3	314175	8.9%
2	230368	6.5%
5	188126	5.3%
1	141803	4.0%
6	72887	2.1%
7	26420	0.7%
8	9738	0.3%
9	3609	0.1%
Other values (30)	3469	0.1%
(Missing)	1634823	46.3%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	587272	16.6%
1	141803	4.0%
2	230368	6.5%
3	314175	8.9%
4	320521	9.1%
5	188126	5.3%
6	72887	2.1%
7	26420	0.7%
8	9738	0.3%
9	3609	0.1%

Value	Count	Frequency (%)
67	1	< 0.1%
56	2	< 0.1%
54	1	< 0.1%
53	3	< 0.1%
50	2	< 0.1%
41	1	< 0.1%
35	2	< 0.1%
34	1	< 0.1%
33	2	< 0.1%
32	2	< 0.1%

code_nature_culture
Categorical

HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct	27
Distinct (%)	< 0.1%
Missing	1112059
Missing (%)	31.5%
Memory size	27.0 MiB

S	1151464
T	359174
P	190040
AB	127433
J	123089
Other values (22)	469952

Length

Max length	2
Median length	1
Mean length	1.197536958
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	S
2nd row	S
3rd row	S
4th row	S
5th row	L

Common Values

Value	Count	Frequency (%)
S	1151464	32.6%
T	359174	10.2%
P	190040	5.4%
AB	127433	3.6%
J	123089	3.5%
BT	103871	2.9%
L	96258	2.7%
AG	84735	2.4%
VI	41396	1.2%
BR	34436	1.0%
Other values (17)	109256	3.1%
(Missing)	1112059	31.5%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
s	1151464	47.6%
t	359174	14.8%
p	190040	7.8%
ab	127433	5.3%
j	123089	5.1%
bt	103871	4.3%
l	96258	4.0%
ag	84735	3.5%
vi	41396	1.7%
br	34436	1.4%
Other values (17)	109256	4.5%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

nature_culture
Categorical

HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct	27
Distinct (%)	< 0.1%
Missing	1112059
Missing (%)	31.5%
Memory size	27.0 MiB

sols	1151464
terres	359174
prés	190040
terrains a bâtir	127433
jardins	123089
Other values (22)	469952

Length

Max length	19
Median length	4
Mean length	6.638552639
Min length	4

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	sols
2nd row	sols
3rd row	sols
4th row	sols
5th row	landes

Common Values

Value	Count	Frequency (%)
sols	1151464	32.6%
terres	359174	10.2%
prés	190040	5.4%
terrains a bâtir	127433	3.6%
jardins	123089	3.5%
taillis simples	103871	2.9%
landes	96258	2.7%
terrains d'agrément	84735	2.4%
vignes	41396	1.2%
futaies résineuses	34436	1.0%
Other values (17)	109256	3.1%
(Missing)	1112059	31.5%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
sols	1151464	39.1%
terres	359282	12.2%
terrains	212168	7.2%
prés	192687	6.5%
a	127433	4.3%
bâtir	127433	4.3%
jardins	123089	4.2%
taillis	121598	4.1%
simples	103871	3.5%
landes	96592	3.3%
Other values (24)	331523	11.2%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

code_nature_culture_speciale
Categorical

HIGH CARDINALITY
MISSING

Distinct	120
Distinct (%)	0.1%
Missing	3375916
Missing (%)	95.5%
Memory size	27.0 MiB

POTAG	34964
PATUR	15855
PARC	13383
PIN	12642
FRICH	10625
Other values (115)	69826

Length

Max length	5
Median length	5
Mean length	4.498534601
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	4 ?
Unique (%)	< 0.1%

Sample

1st row	ACACI
2nd row	FRICH
3rd row	PATUR
4th row	FRICH
5th row	FRICH

Common Values

Value	Count	Frequency (%)
POTAG	34964	1.0%
PATUR	15855	0.4%
PARC	13383	0.4%
PIN	12642	0.4%
FRICH	10625	0.3%
VAOC	7371	0.2%
CHAT	5181	0.1%
IMM	4363	0.1%
CHENE	3885	0.1%
MARAI	3456	0.1%
Other values (110)	45570	1.3%
(Missing)	3375916	95.5%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
potag	34964	22.2%
patur	15855	10.1%
parc	13383	8.5%
pin	12642	8.0%
frich	10625	6.8%
vaoc	7371	4.7%
chat	5181	3.3%
imm	4363	2.8%
chene	3885	2.5%
marai	3456	2.2%
Other values (110)	45570	29.0%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

nature_culture_speciale
Categorical

HIGH CARDINALITY
MISSING

Distinct	120
Distinct (%)	0.1%
Missing	3375916
Missing (%)	95.5%
Memory size	27.0 MiB

Jardin potager	34964
Pâture plantée	15855
Parc	13383
Pins	12642
Friche	10625
Other values (115)	69826

Length

Max length	38
Median length	14
Mean length	12.5603611
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	4 ?
Unique (%)	< 0.1%

Sample

1st row	Acacias
2nd row	Friche
3rd row	Pâture plantée
4th row	Friche
5th row	Friche

Common Values

Value	Count	Frequency (%)
Jardin potager	34964	1.0%
Pâture plantée	15855	0.4%
Parc	13383	0.4%
Pins	12642	0.4%
Friche	10625	0.3%
Vins d'appellation d'origine contrôlée	7371	0.2%
Châtaigneraie	5181	0.1%
Dépendances d'ensemble immobilier	4363	0.1%
Chênes	3885	0.1%
Pré marais	3456	0.1%
Other values (110)	45570	1.3%
(Missing)	3375916	95.5%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
jardin	36478	12.8%
potager	34964	12.2%
pâture	15855	5.5%
plantée	15855	5.5%
parc	13387	4.7%
pins	12642	4.4%
friche	10625	3.7%
ou	8329	2.9%
vins	7549	2.6%
contrôlée	7371	2.6%
Other values (154)	122781	43.0%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

surface_terrain
Real number (ℝ_≥0)

HIGH CORRELATION
MISSING
SKEWED

Distinct	47002
Distinct (%)	1.9%
Missing	1112128
Missing (%)	31.5%
Infinite	0
Infinite (%)	0.0%
Mean	3074.833515

Minimum	1
Maximum	2047961
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	27.0 MiB

Quantile statistics

Minimum	1
5-th percentile	30
Q1	235
median	623
Q3	1930
95-th percentile	12700
Maximum	2047961
Range	2047960
Interquartile range (IQR)	1695

Descriptive statistics

Standard deviation	13291.92486
Coefficient of variation (CV)	4.322811235
Kurtosis	4022.718132
Mean	3074.833515
Median Absolute Deviation (MAD)	500
Skewness	45.59182149
Sum	7444427151
Variance	176675266.6
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
500	46822	1.3%
1000	22377	0.6%
600	6915	0.2%
800	6849	0.2%
12	6148	0.2%
700	5766	0.2%
400	5718	0.2%
13	5609	0.2%
100	5409	0.2%
200	5371	0.2%
Other values (46992)	2304099	65.2%
(Missing)	1112128	31.5%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
1	5124	0.1%
2	4143	0.1%
3	3848	0.1%
4	3956	0.1%
5	4051	0.1%
6	3966	0.1%
7	3688	0.1%
8	3785	0.1%
9	3687	0.1%
10	4781	0.1%

Value	Count	Frequency (%)
2047961	1	< 0.1%
1889207	1	< 0.1%
1662560	1	< 0.1%
1459143	1	< 0.1%
1420388	1	< 0.1%
1411524	14	< 0.1%
1335003	19	< 0.1%
1322177	33	< 0.1%
1250223	1	< 0.1%
1204395	1	< 0.1%

longitude
Real number (ℝ)

HIGH CORRELATION
MISSING

Distinct	1888639
Distinct (%)	54.2%
Missing	51669
Missing (%)	1.5%
Infinite	0
Infinite (%)	0.0%
Mean	2.212156196

Minimum	-63.147439
Maximum	55.83136
Zeros	1
Zeros (%)	< 0.1%
Negative	811107
Negative (%)	23.0%
Memory size	27.0 MiB

Quantile statistics

Minimum	-63.147439
5-th percentile	-2.245149
Q1	0.177443
median	2.321533
Q3	4.395876
95-th percentile	6.605287
Maximum	55.83136
Range	118.978799
Interquartile range (IQR)	4.218433

Descriptive statistics

Standard deviation	6.292895562
Coefficient of variation (CV)	2.844688623
Kurtosis	67.79648593
Mean	2.212156196
Median Absolute Deviation (MAD)	2.117716
Skewness	-1.590094114
Sum	7701714.707
Variance	39.60053455
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
2.459332	1694	< 0.1%
2.288996	1044	< 0.1%
2.169271	1013	< 0.1%
2.395374	971	< 0.1%
2.46163	806	< 0.1%
2.042915	701	< 0.1%
2.324086	687	< 0.1%
2.311923	636	< 0.1%
5.393182	631	< 0.1%
4.33429	502	< 0.1%
Other values (1888629)	3472857	98.3%
(Missing)	51669	1.5%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
-63.147439	1	< 0.1%
-63.142903	4	< 0.1%
-63.14264	4	< 0.1%
-63.138181	1	< 0.1%
-63.136159	8	< 0.1%
-63.133047	1	< 0.1%
-63.133045	1	< 0.1%
-63.13262	6	< 0.1%
-63.132466	3	< 0.1%
-63.115044	3	< 0.1%

Value	Count	Frequency (%)
55.83136	1	< 0.1%
55.830533	1	< 0.1%
55.830446	1	< 0.1%
55.829985	2	< 0.1%
55.829031	1	< 0.1%
55.828607	1	< 0.1%
55.828321	1	< 0.1%
55.827919	1	< 0.1%
55.827727	1	< 0.1%
55.827548	1	< 0.1%

latitude
Real number (ℝ)

HIGH CORRELATION
MISSING

Distinct	1820702
Distinct (%)	52.3%
Missing	51669
Missing (%)	1.5%
Infinite	0
Infinite (%)	0.0%
Mean	46.20441239

Minimum	-21.385063
Maximum	51.082118
Zeros	0
Zeros (%)	0.0%
Negative	17196
Negative (%)	0.5%
Memory size	27.0 MiB

Quantile statistics

Minimum	-21.385063
5-th percentile	43.25579005
Q1	44.808463
median	46.897582
Q3	48.70829
95-th percentile	49.8812955
Maximum	51.082118
Range	72.467181
Interquartile range (IQR)	3.899827

Descriptive statistics

Standard deviation	5.705283676
Coefficient of variation (CV)	0.1234791956
Kurtosis	98.34584576
Mean	46.20441239
Median Absolute Deviation (MAD)	1.901368
Skewness	-9.016514683
Sum	160862602.3
Variance	32.55026183
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
49.037233	1693	< 0.1%
48.688202	1044	< 0.1%
48.757789	1013	< 0.1%
48.713603	971	< 0.1%
48.90182	806	< 0.1%
48.811098	698	< 0.1%
48.957154	691	< 0.1%
43.498437	631	< 0.1%
48.831863	596	< 0.1%
43.823295	502	< 0.1%
Other values (1820692)	3472897	98.3%
(Missing)	51669	1.5%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
-21.385063	1	< 0.1%
-21.384926	1	< 0.1%
-21.384766	1	< 0.1%
-21.384669	1	< 0.1%
-21.384603	1	< 0.1%
-21.384599	1	< 0.1%
-21.38458	1	< 0.1%
-21.38453	1	< 0.1%
-21.384497	1	< 0.1%
-21.384429	1	< 0.1%

Value	Count	Frequency (%)
51.082118	6	< 0.1%
51.082045	4	< 0.1%
51.081947	4	< 0.1%
51.081805	4	< 0.1%
51.081765	2	< 0.1%
51.081631	4	< 0.1%
51.081576	3	< 0.1%
51.081375	6	< 0.1%
51.081102	13	< 0.1%
51.080765	5	< 0.1%

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

A simple visualization of nullity by column.

Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

The dendrogram allows you to more fully correlate variable completion, revealing trends deeper than the pairwise ones visible in the correlation heatmap.

First rows

	id_mutation	date_mutation	numero_disposition	nature_mutation	valeur_fonciere	adresse_numero	adresse_suffixe	adresse_nom_voie	adresse_code_voie	code_postal	code_commune	nom_commune	code_departement	ancien_code_commune	ancien_nom_commune	id_parcelle	ancien_id_parcelle	numero_volume	lot1_numero	lot1_surface_carrez	lot2_numero	lot2_surface_carrez	lot3_numero	lot3_surface_carrez	lot4_numero	lot4_surface_carrez	lot5_numero	lot5_surface_carrez	nombre_lots	code_type_local	type_local	surface_reelle_bati	nombre_pieces_principales	code_nature_culture	nature_culture	code_nature_culture_speciale	nature_culture_speciale	surface_terrain	longitude	latitude
0	2019-1	2019-01-04	1	Vente	37220.0	26.0	NaN	RUE DE MONTHOLON	2730	1000.0	1053	Bourg-en-Bresse	1	NaN	NaN	01053000AI0298	NaN	NaN	8	19.27	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	1	2.0	Appartement	20.0	1.0	NaN	NaN	NaN	NaN	NaN	5.209578	46.198844
1	2019-2	2019-01-04	1	Vente	185100.0	22.0	B	RUE GEN DELESTRAINT	1650	1000.0	1053	Bourg-en-Bresse	1	NaN	NaN	01053000AM0095	NaN	NaN	7	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	1	3.0	Dépendance	NaN	0.0	NaN	NaN	NaN	NaN	NaN	5.219438	46.198784
2	2019-2	2019-01-04	1	Vente	185100.0	22.0	NaN	RUE GEN DELESTRAINT	1650	1000.0	1053	Bourg-en-Bresse	1	NaN	NaN	01053000AM0095	NaN	NaN	137	NaN	154	61.51	NaN	NaN	NaN	NaN	NaN	NaN	2	2.0	Appartement	62.0	3.0	NaN	NaN	NaN	NaN	NaN	5.219438	46.198784
3	2019-3	2019-01-08	1	Vente	209000.0	3.0	NaN	RUE DES CHAMPAGNES	0043	1160.0	1314	Priay	1	NaN	NaN	013140000E1676	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	0	1.0	Maison	90.0	4.0	S	sols	NaN	NaN	940.0	5.282085	45.999533
4	2019-4	2019-01-07	1	Vente	134900.0	5.0	NaN	LOT LE BIOLAY	A003	1370.0	1350	Saint-Étienne-du-Bois	1	NaN	NaN	01350000AA0011	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	0	1.0	Maison	101.0	5.0	S	sols	NaN	NaN	490.0	5.299919	46.293275
5	2019-5	2019-01-03	1	Vente	192000.0	165.0	NaN	ALL DES LIBELLULES	0445	1340.0	1024	Attignat	1	NaN	NaN	01024000AI0094	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	0	1.0	Maison	88.0	4.0	S	sols	NaN	NaN	708.0	5.174787	46.269969
6	2019-6	2019-01-08	1	Vente	45000.0	9.0	NaN	RTE DU VIADUC	0001	1250.0	1106	Cize	1	NaN	NaN	011060000A0086	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	0	1.0	Maison	39.0	2.0	S	sols	NaN	NaN	631.0	5.452134	46.205259
7	2019-6	2019-01-08	1	Vente	45000.0	NaN	NaN	SUR LA LATIE	B017	1250.0	1106	Cize	1	NaN	NaN	011060000A0975	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	0	NaN	NaN	NaN	NaN	L	landes	NaN	NaN	120.0	5.452141	46.205327
8	2019-7	2019-01-04	1	Vente	65000.0	50.0	NaN	RUE DOC NODET	1240	1000.0	1053	Bourg-en-Bresse	1	NaN	NaN	01053000AL0003	NaN	NaN	317	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	1	3.0	Dépendance	NaN	0.0	NaN	NaN	NaN	NaN	NaN	5.220652	46.193394
9	2019-7	2019-01-04	1	Vente	65000.0	50.0	NaN	RUE DOC NODET	1240	1000.0	1053	Bourg-en-Bresse	1	NaN	NaN	01053000AL0003	NaN	NaN	17	NaN	33	67.78	NaN	NaN	NaN	NaN	NaN	NaN	2	2.0	Appartement	69.0	3.0	NaN	NaN	NaN	NaN	NaN	5.220652	46.193394

Last rows

	id_mutation	date_mutation	numero_disposition	nature_mutation	valeur_fonciere	adresse_numero	adresse_suffixe	adresse_nom_voie	adresse_code_voie	code_postal	code_commune	nom_commune	code_departement	ancien_code_commune	ancien_nom_commune	id_parcelle	ancien_id_parcelle	numero_volume	lot1_numero	lot1_surface_carrez	lot2_numero	lot2_surface_carrez	lot3_numero	lot3_surface_carrez	lot4_numero	lot4_surface_carrez	lot5_numero	lot5_surface_carrez	nombre_lots	code_type_local	type_local	surface_reelle_bati	nombre_pieces_principales	code_nature_culture	nature_culture	code_nature_culture_speciale	nature_culture_speciale	surface_terrain	longitude	latitude
3533201	2019-1514866	2019-12-05	1	Vente	17521000.0	32.0	NaN	QUAI DE BETHUNE	0940	75004.0	75104	Paris 4e Arrondissement	75	NaN	NaN	75104000AU0011	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	0	3.0	Dépendance	NaN	0.0	S	sols	NaN	NaN	470.0	2.356730	48.851148
3533202	2019-1514866	2019-12-05	1	Vente	17521000.0	32.0	NaN	QUAI DE BETHUNE	0940	75004.0	75104	Paris 4e Arrondissement	75	NaN	NaN	75104000AU0011	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	0	2.0	Appartement	120.0	5.0	S	sols	NaN	NaN	470.0	2.356730	48.851148
3533203	2019-1514866	2019-12-05	1	Vente	17521000.0	32.0	NaN	QUAI DE BETHUNE	0940	75004.0	75104	Paris 4e Arrondissement	75	NaN	NaN	75104000AU0011	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	0	2.0	Appartement	61.0	4.0	S	sols	NaN	NaN	470.0	2.356730	48.851148
3533204	2019-1514867	2019-10-10	1	Adjudication	610000.0	12.0	NaN	RUE BEAUTREILLIS	0797	75004.0	75104	Paris 4e Arrondissement	75	NaN	NaN	75104000AQ0040	NaN	NaN	2	NaN	35	NaN	NaN	NaN	NaN	NaN	NaN	NaN	2	2.0	Appartement	44.0	2.0	NaN	NaN	NaN	NaN	NaN	2.363886	48.852872
3533205	2019-1514868	2019-12-30	1	Vente	1400000.0	24.0	NaN	RUE SAINT SAUVEUR	8752	75002.0	75102	Paris 2e Arrondissement	75	NaN	NaN	75102000AM0018	NaN	NaN	3	101.40	4	43.7	8	NaN	NaN	NaN	NaN	NaN	3	4.0	Local industriel. commercial ou assimilé	100.0	0.0	NaN	NaN	NaN	NaN	NaN	2.348082	48.866421
3533206	2019-1514868	2019-12-30	1	Vente	1400000.0	24.0	NaN	RUE SAINT SAUVEUR	8752	75002.0	75102	Paris 2e Arrondissement	75	NaN	NaN	75102000AM0018	NaN	NaN	10	43.70	14	55.4	NaN	NaN	NaN	NaN	NaN	NaN	2	2.0	Appartement	97.0	3.0	NaN	NaN	NaN	NaN	NaN	2.348082	48.866421
3533207	2019-1514869	2019-12-17	1	Adjudication	620000.0	14.0	NaN	RUE PAVEE	7195	75004.0	75104	Paris 4e Arrondissement	75	NaN	NaN	75104000AM0014	NaN	NaN	3	48.50	4	NaN	NaN	NaN	NaN	NaN	NaN	NaN	2	2.0	Appartement	45.0	2.0	NaN	NaN	NaN	NaN	NaN	2.360714	48.856181
3533208	2019-1514870	2019-12-05	1	Vente	370000.0	23.0	NaN	RUE POISSONNIERE	7561	75002.0	75102	Paris 2e Arrondissement	75	NaN	NaN	75102000AH0067	NaN	NaN	1	38.65	8	NaN	NaN	NaN	NaN	NaN	NaN	NaN	2	4.0	Local industriel. commercial ou assimilé	47.0	0.0	NaN	NaN	NaN	NaN	NaN	2.347497	48.869727
3533209	2019-1514871	2019-12-12	1	Adjudication	44000.0	2.0	NaN	RUE NOTRE DAME DES VICTOIRES	6840	75002.0	75102	Paris 2e Arrondissement	75	NaN	NaN	75102000AJ0127	NaN	NaN	41	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	1	3.0	Dépendance	NaN	0.0	NaN	NaN	NaN	NaN	NaN	2.341246	48.866478
3533210	2019-1514872	2019-12-26	1	Vente	25000.0	17.0	NaN	RUE BLONDEL	1021	75002.0	75102	Paris 2e Arrondissement	75	NaN	NaN	75102000AP0053	NaN	NaN	34	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	1	2.0	Appartement	4.0	1.0	NaN	NaN	NaN	NaN	NaN	2.353082	48.868707

Overview

Variables

Common Values

Length

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Most occurring characters

Most occurring categories

Most frequent character per category